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A finite simple graph is bipartite if and only if its adjacency spectrum is symmetric about
Statement
Let be a finite simple graph with adjacency spectrum . Then is bipartite if and only if the multiset is symmetric about , that is, if and only if as multisets.
Facts & Assumptions
Given: A finite simple graph with adjacency matrix and adjacency spectrum .
In a bipartite graph the vertex set splits as , and every edge joins a vertex of to a vertex of (A bipartite graph and a proper two-colouring of its vertices).
A graph is bipartite exactly when it has no odd cycle (A finite graph is bipartite if and only if it has no odd cycle).
The trace counts closed walks of length (The trace of counts closed walks of length ).
The adjacency spectrum is the multiset of eigenvalues of (Adjacency spectrum, spectral radius, and cospectral graphs).
Similar matrices have the same trace (Similar matrices have the same trace).
Proof
Assume first that is bipartite with parts and . Let be the diagonal matrix whose entry is on and on . Then , and [F1] shows that every edge changes sign across the partition, so . Hence and are similar and therefore have the same eigenvalues. By [F2], the spectrum is symmetric about .
Conversely, assume the spectrum is symmetric about . Because [F2] cites the real spectral theorem for the real symmetric matrix , there is an invertible matrix with . For every odd integer , this gives , so [L3] yields after the odd powers cancel in symmetric pairs. By [L2], has no closed walk of odd length. An odd cycle would itself be an odd closed walk, so has no odd cycle. Therefore [L1] makes bipartite.
Steps 1.1 and 1.2 prove the two directions of the equivalence.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
21 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Steve Butler, Spectral Graph Theory course notes, lectures 3-4 (standard reference, not scraped)